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My slides are up on this repo: (I also use this repo in similar reproducibility talks where I'm demonstrating github) I use this content in a lot of different contexts now (undergrad course, our Café Code series, a grad course run from Norway, OHW...), and I'm regularly updating it. |
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Awesome! I'm glad these presentations are living beyond their original intent! Give me a shout if you need help putting something more formal together. FYI, it looks like my slides are now in the OHW21 branch: https://github.com/oceanhackweek/ohw-tutorials/blob/OHW21/reproducible-science/reproducible_science_2021.pdf |
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On February 27 - March 4, 2023, we had an OceanHackWeek event in Spanish. There, @LauraGomezNavarro gave a great presentation on open science and reproducibility -- in Spanish, of course! She looked at previous OHW presentations on the topic and used some of the materials, but she added great new perspectives and materials. So, we're adding to the OHW resources on reproducibility and open science, now with a new, fresh perspective and in Spanish. Here are the presentation and YouTube recording. ¡Gracias Laura! |
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Thanks for catching the link error, @LauraGomezNavarro . I've fixed it on my original posting. |
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The latest addition to the OHW presentations on reproducibility and open science took place on August 7 at OceanHackWeek 2023. See Joseph Gum's (@asx-) presentation materials and link to the YouTube recording here: "(Digital) Reproducible Science" |
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At OHW we've had a presentation on reproducibility in ocean research and data science every year, at least since 2019. These cover motivation, best practices, software tools, community resources, and lots more. Each year the presentation has been at least a bit different. In particular, this year's (2022) presentation by @SeascapeScience (Nick Record) and the 2021 presentation by @MathewBiddle (Matt Biddle) are nicely complementary. Taken together, they make for a great introduction to reproducibility for ocean data science.
@SeascapeScience and @MathewBiddle, please chime in if I mischaracterized anything.
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